Evidence map›Paper›PMID 29112986›Full record

ArticlePloS one2017

Simultaneous genome-wide gene expression and transcript isoform profiling in the human malaria parasite.

Lindsey B Turnbull, Geoffrey H Siwo, Katrina A Button-Simons, Asako Tan, Lisa A Checkley, Heather J Painter, Manuel Llinás, Michael T Ferdig

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Lindsey B TurnbullDepartment of Biological Sciences, Eck Institute for Global Health, University of Notre Dame, Notre Dame, Indiana, United States of America.ORCID http://orcid.org/0000-0002-5192-8867
Geoffrey H SiwoDepartment of Biological Sciences, Eck Institute for Global Health, University of Notre Dame, Notre Dame, Indiana, United States of America.
Katrina A Button-SimonsDepartment of Biological Sciences, Eck Institute for Global Health, University of Notre Dame, Notre Dame, Indiana, United States of America.
Asako TanDepartment of Biological Sciences, Eck Institute for Global Health, University of Notre Dame, Notre Dame, Indiana, United States of America.
Lisa A CheckleyDepartment of Biological Sciences, Eck Institute for Global Health, University of Notre Dame, Notre Dame, Indiana, United States of America.
Heather J PainterDepartment of Biochemistry & Molecular Biology and Center for Malaria Research, Pennsylvania State University, University Park, Pennsylvania, United States of America.
Manuel LlinásDepartment of Biochemistry & Molecular Biology and Center for Malaria Research, Pennsylvania State University, University Park, Pennsylvania, United States of America.
Michael T FerdigDepartment of Biological Sciences, Eck Institute for Global Health, University of Notre Dame, Notre Dame, Indiana, United States of America.

Funding

Spatial Patterning During DevelopmentP50GM071508 · NIGMS · PRINCETON UNIVERSITY · PI POWELL, SUSAN M · 2004 to 2013
$30.6M
Indiana Clinical and Translational Sciences InstituteUL1TR001108 · NCATS · INDIANA UNIVERSITY INDIANAPOLIS · PI DENNE, SCOTT C., SHEKHAR, ANANTHA · 2013 to 2017
$23.3M
A network-based method for predicting gene interactions in artemisinin resistanceR21AI111286 · NIAID · UNIVERSITY OF NOTRE DAME · PI FERDIG, MICHAEL T · 2015 to 2016
$418k
NCATS NIH HHS UL1 TR001108NIAID NIH HHS R21 AI111286NIGMS NIH HHS P50 GM071508
6 · The paper itself

Abstract

Gene expression DNA microarrays have been vital for characterizing whole-genome transcriptional profiles. Nevertheless, their effectiveness relies heavily on the accuracy of genome sequences, the annotation of gene structures, and the sequence-dependent performance of individual probes. Currently available gene expression arrays for the malaria parasite Plasmodium falciparum rely on an average of 2 probes per gene, usually positioned near the 3' end of genes; consequently, existing designs are prone to measurement bias and cannot capture complexities such as the occurrence of transcript isoforms arising from alternative splicing or alternative start/ stop sites. Here, we describe two novel gene expression arrays with exon-focused probes designed with an average of 12 and 20 probes spanning each gene. This high probe density minimizes signal noise inherent in probe-to-probe sequence-dependent hybridization intensity. We demonstrate that these exon arrays accurately profile genome-wide expression, comparing favorably to currently available arrays and RNA-seq profiling, and can detect alternatively spliced transcript isoforms as well as non-coding RNAs (ncRNAs). Of the 964 candidate alternate splicing events from published RNA-seq studies, 162 are confirmed using the exon array. Furthermore, the exon array predicted 330 previously unidentified alternate splicing events. Gene expression microarrays continue to offer a cost-effective alternative to RNA-seq for the simultaneous monitoring of gene expression and alternative splicing events. Microarrays may even be preferred in some cases due to their affordability and the rapid turn-around of results when hundreds of samples are required for fine-scale systems biology investigations, including the monitoring of the networks of gene co-expression in the emergence of drug resistance.

Indexed as

Gene ExpressionAlternative SplicingAnimalsExonsHumansOligonucleotide Array Sequence AnalysisPlasmodiumRNA, MessengerRNA, Messenger

Identifiers

PMID29112986
PMCPMC5675406

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.